Airborne Disease Propagation on Large Scale Social Contact Networks

Shahzamal,; Jurdak, Raja; Arablouei, Reza; Kim, Minkyoung; Thilakarathna, Kanchana; Mans, Bernard

doi:10.1145/3055601.3055604

Cited by 14 publications

(30 citation statements)

References 22 publications

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“…We vary the value of P from 0 to 1 with the step 0.1. The seed nodes start infecting at T = 0 and continue infecting for the period of days picked up randomly from the range (1,5). With this set of seed nodes, we run simulations on the both SPST and SPDT networks and repeat 200 times for each value of P. We set the mean value of b to 0.01min −1 and the median of g to 1h −1 .…”

Section: Results and Analysismentioning

confidence: 99%

“…This process can be explained with an example of airborne disease spreading where an infected individual deposits infectious particles at the locations where they visit. These particles can transmit to susceptible individuals who visit the locations even after the infected individual leaves as the airborne infectious particles suspend in the air for a long time [3,5]. Therefore, susceptible individuals do not need to be in the same place at the same time with the infected individual to contract disease.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Shahzamal

Jurdak

Mans

et al. 2018

Lecture Notes in Computer Science

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Interaction patterns among individuals play vital roles in spreading infectious diseases. Understanding these patterns and integrating their impact in modeling diffusion dynamics of infectious diseases are important for epidemiological studies. Current network-based diffusion models assume that diseases transmit through interactions where both infected and susceptible individuals are co-located at the same time. However, there are several infectious diseases that can transmit when a susceptible individual visits a location after an infected individual has left. Recently, we introduced a diffusion model called same place different time (SPDT) transmission to capture the indirect transmissions that happen when an infected individual leaves before a susceptible individual's arrival along with direct transmissions. In this paper, we demonstrate how these indirect transmission links significantly enhance the emergence of infectious diseases simulating airborne disease spreading on a synthetic social contact network. We denote individuals having indirect links but no direct links during their infectious periods as hidden spreaders. Our simulation shows that indirect links play similar roles of direct links and a single hidden spreader can cause large outbreak in the SPDT model which causes no infection in the current model based on direct link. Our work opens new direction in modeling infectious diseases.

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Section: Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Shahzamal

Jurdak

Mans

et al. 2018

Lecture Notes in Computer Science

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“…We also assumed that the coexistence should last longer than 20 s. In case shorter encounters should be monitored as well, we will have to evaluate the impact of the window size over which the correlation is computed. Finally, the `same-place-different-time (SPDT)’ disease transmissions [ 31 ] (or `co-location’ [ 30 ]) will be an interesting extension of the current work. We believe such contact types will be detected by coping with time gaps and distortions stemming from moving speed differences and detours.…”

Section: Discussionmentioning

confidence: 99%

“…Note that the type of contact we aim to detect in this paper is coexistence, or `trajectory bundle’ [ 30 ]. It is because this `same-place-same-time’ (SPST) contact type is more common in infectious disease transmissions than the `same-place-different-time’ (SPDT) type [ 31 ] (not to mention social contacts). Since the smartphone users are assumed to stay/move together in this type of contact, we do not need to align the traces for the time gap and the moving speed differences by using such schemes as Dynamic Time Window (DTW).…”

Section: Methodsmentioning

confidence: 99%

Empirical Determination of Efficient Sensing Frequencies for Magnetometer-Based Continuous Human Contact Monitoring

Kuk

Kim

Park

et al. 2018

Sensors

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The high linear correlation between the smartphone magnetometer readings in close proximity can be exploited for physical human contact detection, which could be useful for such applications as infectious disease contact tracing or social behavior monitoring. Alternative approaches using other capabilities in smartphones have aspects that do not fit well with the human contact detection. Using Wi-Fi or cellular fingerprints have larger localization errors than close human contact distances. Bluetooth beacons could reveal the identity of the transmitter, threatening the privacy of the user. Also, using sensors such as GPS does not work for indoor contacts. However, the magnetometer correlation check works best in human contact distances that matter in infectious disease transmissions or social interactions. The omni-present geomagnetism makes it work both indoors and outdoors, and the measured magnetometer values do not easily reveal the identity and the location of the smartphone. One issue with the magnetometer-based contact detection, however, is the energy consumption. Since the contacts can take place anytime, the magnetometer sensing and recording should be running continuously. Therefore, how we address the energy requirement for the extended and continuous operation can decide the viability of the whole idea. However, then, we note that almost all existing magnetometer-based applications such as indoor location and navigation have used high sensing frequencies, ranging from 10 Hz to 200 Hz. At these frequencies, we measure that the time to complete battery drain in a typical smartphone is shortened by three to twelve hours. The heavy toll raises the question as to whether the magnetometer-based contact detection can avoid such high sensing rates while not losing the contact detection accuracy. In order to answer the question, we conduct a measurement-based study using independently produced magnetometer traces from three different countries. Specifically, we gradually remove high frequency components in the traces, while observing the correlation changes. As a result, we find that the human coexistence detection indeed tends to be no less, if not more, effective at the sampling frequency of 1 Hz or even less. This is because unlike the other applications that require centimeter-level precision, the human contacts detected anywhere within a couple of meters are valid for our purpose. With the typical smartphone battery capacity and at the 1 Hz sensing, the battery consumption is well below an hour, which is smaller by more than two hours compared with 10 Hz sampling and by almost eleven hours compared with 200 Hz sampling. With other tasks running simultaneously on smartphones, the energy saving aspect will only become more critical. Therefore, we conclude that sensing the ambient magnetic field at 1 Hz is sufficient for the human contact monitoring purpose. We expect that this finding will have a significant practicability implication in the smartphone magnetometer-based contact monitoring applications in ...

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“…Another limitation of current contact-based vaccination strategies is that they only focus on direct contacts between individuals. Our recent work [17][18][19][20] introduced the concept of indirect transmission, where disease can transmit through indirect interaction (in addition to direct interactions), which is representative of many infectious diseases. For example, a acknowledge the Distributed Sensing System Group, Data61, CSIRO for providing research facilities for this research.…”

Section: Introductionmentioning

confidence: 99%

Vaccination strategies on dynamic networks with indirect transmission links and limited contact information

et al. 2020

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Infectious diseases are still a major global burden for modern society causing 13 million deaths annually. One way to reduce the morbidity and mortality rates from infectious diseases is through pre-emptive or targeted vaccinations. Current theoretical vaccination strategies based on contact networks, however, rely on highly specific individual contact information which is difficult and costly to obtain, in order to identify influential spreading individuals. Current approaches also focus only on direct contacts between individuals for spreading, and disregard indirect transmission where a pathogen can spread between one infected individual and one susceptible individual who visit the same location within a short time-frame without meeting. This paper presents a novel vaccination strategy which relies on coarse-grained contact information, both direct and indirect, that can be easily and efficiently collected. Rather than tracking exact contact degrees of individuals, our strategy uses the types of places people visit to estimate a range of contact degrees for individuals, considering both direct and indirect contacts. We conduct extensive computer simulations to evaluate the performance of our strategy in comparison to state-of-the-art vaccination strategies. Results show that, when considering indirect links, our lower cost vaccination strategy achieves comparable performance to the contact-degree based approach and outperforms other existing strategies without requiring over-detailed information.

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Airborne Disease Propagation on Large Scale Social Contact Networks

Cited by 14 publications

References 22 publications

Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Empirical Determination of Efficient Sensing Frequencies for Magnetometer-Based Continuous Human Contact Monitoring

Vaccination strategies on dynamic networks with indirect transmission links and limited contact information

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